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Mikrosymulacja stochastyczna×Dynamika Systemów Stochastycznych×
DziedzinaSymulacjaSymulacja
RodzinaProcess / pipelineProcess / pipeline
Rok powstania19571980s–2000s
TwórcaGuy H. OrcuttJay W. Forrester (base SD); stochastic extensions developed through 1980s–2000s by multiple researchers
TypStochastic individual-level simulationContinuous stochastic simulation
Źródło pierwotneOrcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123. DOI ↗Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
Inne nazwyProbabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSMSSD, stochastic stock-flow modelling, probabilistic system dynamics, random system dynamics
Pokrewne65
PodsumowanieStochastic Microsimulation tracks a large population of individual units — people, households, or firms — through time by applying random draws from empirically estimated probability distributions at each transition event. Unlike deterministic counterparts, every state change is decided by chance, preserving realistic heterogeneity and allowing rigorous uncertainty quantification across multiple simulation runs.Stochastic System Dynamics (SSD) extends conventional system dynamics by replacing fixed parameter values and deterministic flow equations with probability distributions and random draws. Running many replications of the stock-flow model yields probabilistic trajectories — confidence bands rather than single lines — enabling rigorous uncertainty quantification and risk analysis in complex feedback systems such as epidemic models, supply chains, and energy policy scenarios.
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ScholarGatePorównaj metody: Stochastic Microsimulation · Stochastic System Dynamics. Pobrano 2026-06-15 z https://scholargate.app/pl/compare